doi:10.1073/pnas.2003634119>. No extraneous inputs, distributional assumptions, iterative procedures nor optimization criteria are employed. This package includes functions for computing local depths and cohesion as well as flexible functions for plotting community networks and displays of cohesion against distance.">

pald: Partitioned Local Depth for Community Structure in Data (original) (raw)

Implementation of the Partitioned Local Depth (PaLD) approach which provides a measure of local depth and the cohesion of a point to another which (together with a universal threshold for distinguishing strong and weak ties) may be used to reveal local and global structure in data, based on methods described in Berenhaut, Moore, and Melvin (2022) <doi:10.1073/pnas.2003634119>. No extraneous inputs, distributional assumptions, iterative procedures nor optimization criteria are employed. This package includes functions for computing local depths and cohesion as well as flexible functions for plotting community networks and displays of cohesion against distance.

Version: 0.0.5
Depends: R (≥ 2.10)
Imports: igraph, graphics, glue
Suggests: testthat (≥ 3.0.0)
Published: 2025-05-30
DOI: 10.32614/CRAN.package.pald
Author: Katherine Moore ORCID iD [aut], Kenneth Berenhaut [aut], Lucy D'Agostino McGowanORCID iD [aut, cre]
Maintainer: Lucy D'Agostino McGowan
BugReports: https://github.com/LucyMcGowan/pald/issues
License: MIT + file
URL: https://github.com/LucyMcGowan/pald
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: pald results

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